How Much do Robots Understand Rudeness? Challenges in Human-Robot Interaction

This paper concerns the pressing need to understand and manage inappropriate language within the evolving human-robot interaction (HRI) landscape. As intelligent systems and robots transition from controlled laboratory settings to everyday households, the demand for polite and culturally sensitive conversational abilities becomes paramount, especially for younger individuals. This study explores data cleaning methods, focusing on rudeness and contextual similarity, to identify and mitigate inappropriate language in real-time interactions. State-of-the-art natural language models are also evaluated for their proficiency in discerning rudeness. This multifaceted investigation highlights the challenges of handling inappropriate language, including its tendency to hide within idiomatic expressions and its context-dependent nature. This study will further contribute to the future development of AI systems capable of engaging in intelligent conversations and upholding the values of courtesy and respect across diverse cultural and generational boundaries.

Publication Details

Journal
Edinburgh Napier Research Repository (Edinburgh Napier University)
Published
2024-12-31
Primary Topic
Social Robot Interaction and HRI
Type
article
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article

How Much do Robots Understand Rudeness? Challenges in Human-Robot Interaction

Edinburgh Napier Research Repository (Edinburgh Napier University)
Social Robot Interaction and HRI
article

How Much do Robots Understand Rudeness? Challenges in Human-Robot Interaction

article en

Abstract

This paper concerns the pressing need to understand and manage inappropriate language within the evolving human-robot interaction (HRI) landscape. As intelligent systems and robots transition from controlled laboratory settings to everyday households, the demand for polite and culturally sensitive conversational abilities becomes paramount, especially for younger individuals. This study explores data cleaning methods, focusing on rudeness and contextual similarity, to identify and mitigate inappropriate language in real-time interactions. State-of-the-art natural language models are also evaluated for their proficiency in discerning rudeness. This multifaceted investigation highlights the challenges of handling inappropriate language, including its tendency to hide within idiomatic expressions and its context-dependent nature. This study will further contribute to the future development of AI systems capable of engaging in intelligent conversations and upholding the values of courtesy and respect across diverse cultural and generational boundaries.

Edinburgh Napier Research Repository (Edinburgh Napier University)
Quality Education
Openalex Percentile: Top 41%
Social Robot Interaction and HRI
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